Consider the simple linear regression model Yi = βxi + ϵi, for i = 1, …, n; where E(ϵi) = 0, Cov(ϵi, ϵk) = 0 if i ≠ k and Var(ϵi) = \(\rm x_i^2 \sigma^2\). The best linear unbiased estimator of β is:

1
\(\rm\frac{\displaystyle\sum_{i=1}^n Y_i x_i}{\displaystyle\sum_{i=1}^n x_i^2}\)
2
\(\rm\frac{\displaystyle\sum_{i=1}^n Y_i}{\displaystyle\sum_{i=1}^n x_i}\)
3
\(\rm\frac{1}{n}\displaystyle\sum_{i=1}^n \frac{Y_i}{x_i}\)
4
\(\rm\frac{1}{n}\displaystyle\sum_{i=1}^n \frac{Y_i x_i}{x_i^2}\)

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